Real-world opioid use among patients with migraine enrolled in US commercial insurance and risk factors associated with migraine progression

BACKGROUND: Migraineurs may be categorized as having episodic migraine (EM: < 15 headache days/month) or chronic migraine (CM: ≥ 15 days/month for > 3 months with ≥ 8 days/month having features of migraine). Opioid use has been linked to progression from EM to CM. OBJECTIVE: To describe the utilization of opioid prescriptions among patients with migraine, to determine the association between opioid use and migraine progression, and to explore demographic and clinical risk factors for migraine progression. METHODS: This retrospective cohort study used Optum’s deidentified Clinformatics Data Mart Database from January 2015 to December 2018. Adult patients with a migraine diagnosis and continuous health plan enrollment were included. Opioid use was measured by average daily morphine equivalent dose, also known as morphine milligram equivalent (MME). Descriptive statistics were used to summarize the opioid use by patient demographic and clinical characteristics. A Cox proportional hazards model with stepwise selection was used to determine the risk factors of new-onset CM. RESULTS: Overall, 35% of patients with migraine (27,331 of 78,134) received prescription opioids (> 0 MME/day) during the 12-month follow-up period. Higher opioid dosage was found in patients who had CM and comorbidities of interest. Compared with patients with EM, patients with CM were twice as likely to receive at least 20 MME/day (CM 3.8% vs EM 1.9%) and had a higher median opioid day supply (CM 20 vs EM 10) during follow-up. About 7% of patients with CM with at least 1 opioid prescription had at least 50 MME/day in any 90-day period during follow-up. A significant association was found between MME level and the likelihood of new-onset CM. Additional significant risk factors of migraine progression included younger age, female sex, South and West regions, and having a diagnosis of medication overuse headache, depression, back pain, or fibromyalgia (all P < 0.05). CONCLUSIONS: Despite guidelines and the availability of more migraine-specific treatments, opioids are still commonly prescribed to patients with migraines in real-world practice, especially for those with CM. In this study population, a higher risk of new-onset CM was associated with receiving higher opioid doses.

METHODS: This retrospective cohort study used Optum's deidentified Clinformatics Data Mart Database from January 2015 to December 2018. Adult patients with a migraine diagnosis and continuous health plan enrollment were included. Opioid use was measured by average daily morphine equivalent dose, also known as morphine milligram equivalent (MME). Descriptive statistics were used to summarize the opioid use by patient demographic and clinical characteristics. A Cox proportional hazards model with stepwise selection was used to determine the risk factors of new-onset CM.

RESULTS:
Overall, 35% of patients with migraine (27,331 of 78,134) received prescription opioids (> 0 MME/day) during the 12-month follow-up period. Higher opioid dosage was found in patients who had CM and comorbidities of interest. Compared with patients with EM, patients with CM were

Plain language summary
Migraine treatment guidelines do not recommend using opioids because of limited efficacy and risk of overuse. However, about one-third of patients with migraine are given opioids in clinical practice. This study used a standardized method (published by the Centers for Disease Control and Prevention) to calculate opioid doses in patients with migraine, including both chronic and episodic types. Additionally, this study explored potential risk factors for migraine progression. This helps increase the awareness of opioid use and aids in understanding the progression in patients with migraine.

Implications for managed care pharmacy
Despite guidelines and the availability of migraine-specific medications, opioids are still prescribed in more than one-third of patients with migraine. This study showed that a higher opioid dose (based on the average daily morphine equivalent dose) is associated with an increased risk of progression to chronic migraine. Although the opioid itself is relatively inexpensive, it is associated with disease progression and, thus, higher downstream health care utilization and costs. Payers and health care providers should continue educating patients on opioid risk and use migraine-specific medications to optimize long-term patient outcomes.
Migraine is a common primary headache disorder. Approximately 15% of Americans experience migraine, with higher prevalence found in women and middle-age populations. 1 Patients can be broadly categorized into episodic migraine (EM) if they have fewer than 15 headache days per month or chronic migraine (CM) if they have 15 or more headache days per month for more than 3 months (with ≥ 8 days/month having features of migraine headache). 2 Patients with EM can transition to CM if they are exposed to certain modifiable (eg, overuse of acute medications or obesity) or nonmodifiable (eg, sex or age) risk factors, and this process is called migraine progression or migraine chronification. [3][4][5] The estimated annual conversion rate from EM to CM is approximately 3%. 4 Evidence has shown that opioids are commonly used among patients with migraine (about 33%-36%), especially in emergency department (ED) settings. [6][7][8] The use of opioids for migraine has been linked to medication overuse headache (MOH) (other acute medications could also cause MOH, for example, analgesics), more severe headacherelated disability, and greater health care utilization. 7,9 Although opioids themselves are relatively inexpensive, studies found that patients who use opioids are 2.1 times more likely to have a future migraine-related ED visit 10 and 1.5 to 3 times more likely to be in the upper quartile group in terms of annual health care costs. 11 In other words, opioid use among patients with migraine is associated with substantial economic burden for payers and patients.
Previous studies assessing the use of opioids for migraine treatment mainly considered opioid use as a binary factor (whether opioids were prescribed) or as the number of opioid prescriptions, [6][7][8]10,11 the results of which may vary depending on the type and strength of opioids. A more standardized and precise approach to quantify opioid use is to calculate patients' average daily morphine equivalent dose (MED), which converts the quantity and doses of various prescription opioids into one standard value allowing for comparisons. 4 It is important to further understand the association of opioid use with migraine progression and explore additional modifiable risk factors that could provide insights in clinical intervention.
The purpose of this study was to (1) describe the recent utilization patterns of opioid prescriptions (in terms of MED) among patients with migraine enrolled in commercial insurance plans, (2) determine the relationship between opioid use and new-onset CM, and (3) explore the demographic and clinical risk factors for migraine progression.

DATA SOURCE
The Optum Clinformatics Data Mart ("Optum") commercial claims database from January 1, 2015, to December 31, 2018, was used for conducting retrospective analysis. The deidentified database was obtained from The University of Texas Health Science Center at Houston. Data files include the eligibility table, medical claims, and pharmacy claims for more than 111 million lives. Optum data are national in scope, which represents patients enrolled in one of the largest commercial health plans in the United States. The database is constructed from a variety of geographic regions and employers, which makes it retain a level of diversity while representing the overall trend in commercial health plan coverage. 12 The eligibility table contains patient enrollment and demographic information. The medical claims table contains claim-level information, such as diagnosis, place of service, and date of service. The pharmacy table contains outpatient prescription information, such as generic and brand name, National Drug Code number, fill date, days supply, strength, and quantity.
This study was approved by the institutional review board of The University of Texas at Austin and The University of Texas Health Science Center at Houston.

PATIENT SELECTION
The index date was defined as the date of the first diagnosis (CM or EM). The study objectives required different inclusion/exclusion criteria (Supplementary Table 1, available in online article). Specifically for objective 1 (describe opioid use), patients were grouped into CM or EM, with patients with EM not having any CM diagnosis in the entire study period (6 months pre-and 12 months post-index). Alternatively, for objectives 2 and 3 (risk factors for new-onset CM), patients twice as likely to receive at least 20 MME/day (CM 3.8% vs EM 1.9%) and had a higher median opioid day supply (CM 20 vs EM 10) during follow-up. About 7% of patients with CM with at least 1 opioid prescription had at least 50 MME/day in any 90-day period during follow-up. A significant association was found between MME level and the likelihood of new-onset CM. Additional significant risk factors of migraine progression included younger age, female sex, South and West regions, and having a diagnosis of medication overuse headache, depression, back pain, or fibromyalgia (all P < 0.05).

CONCLUSIONS:
Despite guidelines and the availability of more migraine-specific treatments, opioids are still commonly prescribed to patients with migraines in real-world practice, especially for those with CM. In this study population, a higher risk of new-onset CM was associated with receiving higher opioid doses. average, the difference in post-index duration was then adjusted (lowered) if the transition to CM occurred before the follow-up period ended.
For objectives 2 and 3, new-onset CM was defined as the first CM diagnosis after the index date of EM and during the 24-month follow-up period. The time to new-onset CM was then measured as the number of days from the index date until the earliest CM diagnosis. Patients who did not have a diagnosis of CM throughout the post-index period were censored at the end of the 24-month follow-up period. Since sample size was small for patients in the 90-200 MME/day group and the greater than 200 MME/day group, patients with at least 50 MME/day were combined into one category when modeling.

DEMOGRAPHIC AND CLINICAL CHARACTERISTICS
Demographic and clinical characteristics during the preindex period were identified. Demographic variables included age, sex, and region. Clinical characteristics included Charlson comorbidity index (CCI) score and some additional comorbidities of interest (chronic pain, back pain, MOH, opioid use disorder, depression, anxiety, fibromyalgia, epilepsy, hypertension, irritable bowel syndrome, and osteoarthritis).

STATISTICAL ANALYSES
Descriptive statistics (mean, SD, median, quartile, frequency, percentage) were used to describe the utilization of opioids by patient characteristics (objective 1). Unadjusted and adjusted Cox proportional hazards regressions were used to model the time to new-onset CM. In the unadjusted model, the opioid use group was the only predictor (objective 2). In the adjusted model, additional predictors were incorporated, including age, sex, region, CCI score, and whether patients had each additional comorbidity (objective 3). A stepwise selection approach was used in the adjusted model to create a more parsimonious model (default P < 0.15 for variable inclusion and retention). Proportional hazards assumptions were tested by creating time-dependent covariates in the Cox model and checking whether the interaction terms were significant. 19 An α level of 0.05 was set a priori for statistical significance, and all tests were two sided. All analyses were performed with the use of SAS Version 9.4 (SAS Institute Inc).
with EM did not have a CM diagnosis during the pre-index period (6 months before index date), but they could transition to CM during the follow-up period (24 months after the index date). Note that the durations of follow-up were different: objective 1 required at least 12 months' follow-up whereas objectives 2 and 3 required at least 24 months' follow-up to capture more patients who may transition to CM.
Disease diagnoses were based on the International Classification of Diseases (ICD), Ninth Revision and Tenth Revision, which were available in the medical claims

STUDY VARIABLES
Opioid Use. Utilization of opioid prescriptions was mainly calculated based on the average daily MED during the post-index period, which is also known as the morphine milligram equivalent (MME). 15 This approach allows us to directly compare the usage of different opioids by converting various prescription opioids and strengths into one standardized value. 15 The calculation of MED is based on a toolkit provided by the US Department of Health & Human Services (HHS) toolkit in 2018 and the MME conversion factors published by the Centers for Disease Control and Prevention. 15 The HHS toolkit also provides SAS programming codes that can be used to calculate opioid levels and identify patients at risk of misuse or overdose. Below are the calculation formulas 15 : The formula for calculating MED per prescription is as follows: (Strength per unit)×

MED = (Quantity dispensed)×(MME conversion factor) (Days supply)
The average daily MED can then be calculated by the following formula:

Total MED of all Average daily MED = prescriptions in the time frame Total number of days in the time frame
For objective 1, a fixed duration of 365 days (post-index) was used as the denominator for calculating the average daily MED for each patient. For objectives 2 and 3, the time frame of calculating the average daily MED was defined to start from the index date (first diagnosis of EM) to when they transitioned to CM or to the end of the follow-up period (24 months post-index), whichever came first. The MED measurement was calculated before patients transitioned to CM, because patients may have had different opioid use patterns once they progressed to CM. Because opioid use is calculated based on a daily The proportion of patients who received opioids increased monotonically with age. Patients in the Northeast were the least likely to receive any prescription opioids compared with patients from other regions (Midwest: 33.1%, Northeast: 23.9%, South: 38.7%, and West: 34.6%). In terms of comorbid conditions, compared with patients who did not have prescription opioids during follow-up, patients who received opioids had higher average CCI scores and were more likely to have each type of those additional comorbidities, especially for those with at least 20 MME/ day (Table 1).
Opioid use among patients with more than 0 MME/day during follow-up stratified by migraine type is provided in Table 2. Most patients with at least 1 opioid prescription received less than 20 MME/day during follow-up (EM = 94.3% vs CM = 90.6%). Compared with patients with

OBJECTIVE 1: DESCRIBE OPIOID USE AMONG PATIENTS WITH CM AND EM
A total of 78,134 patients (CM N = 16,588 and EM N = 61,546) met the inclusion/exclusion criteria and were included in the analyses for objective 1. Figure 1 displays the patient attrition process. Table 1 summarizes the opioid use (average daily MME) by patient characteristics. Overall, 35.0% of patients received prescription opioids (> 0 MME/day) during the 12-month follow-up period. Compared with patients with EM, a higher proportion of patients with CM received prescription opioids (CM = 40.8% vs EM = 33.4%). In addition, patients with CM were about twice as likely as patients with EM to receive at least 20 MME/day (CM = 3.8% vs EM = 1.9%) during follow-up.

OBJECTIVE 3: ASSOCIATION OF FACTORS AND TIME TO TRANSITION TO NEW-ONSET CM
The association between demographic and clinical factors and the time to transition from EM to CM was assessed. From both unadjusted (with opioid use group as the only predictor) and adjusted (controlling for covariates) models, compared with patients with less than 1 MME/day, the hazard ratios of progressing to CM were significantly higher among patients with a higher opioid use level (all P < 0.001). In the unadjusted model, the hazard ratios increased as patients fell into a higher opioid use level. Hazard ratios were 1.61 (95% CI = 1.44-1.79) for 1-20 MME/day; 1.73 (95% CI = 1.30-2.31) for 20-50 MME/day; and 1.90 (95% CI = 1.46-2.47) for at least 50 MME/day, with less than 1 MME/day as the reference group (all P < 0.001). Results of the adjusted analysis are presented in Table 4. In the adjusted analysis, higher opioid use was again associated with higher hazard ratios of new-onset CM. Other significant covariates include younger age, female sex, South and West regions, and having a diagnosis of MOH, hypertension, depression, back pain, and fibromyalgia (all P < 0.05). Results from the adjusted model are summarized in Table 4.

Discussion
This study assessed opioid use among patients with EM and CM who were enrolled in US commercial health plans and stratified by patient characteristics (objective 1). In addition, this study evaluated the association of opioid use (in terms of MED) on migraine progression and further examined several additional risk factors of new-onset CM (objectives 2 and 3). The results from objective 1 showed that opioid use was higher in patients with CM, which informed our objectives 2 and 3 to further demonstrate the impact of opioid use on migraine progression. Higher opioid doses were found in patients who had CM (vs EM); were older; and had comorbidities of interest, including MOH, depression, back pain, and fibromyalgia. Significant risk factors of new-onset CM included higher average daily MME use, younger age, female sex, South and West regions, and diagnosis of MOH, depression, hypertension, back pain, and fibromyalgia. EM, patients with CM had a higher median opioid days supply (EM = 10 vs CM = 20; P < 0.0001). Patients with a high and an extreme amount of opioid use, as well as patients who appeared to be doctor shopping as defined in the HHS toolkit, 15 were identified, as these patients were considered to have a higher risk of opioid misuse or overdose. A small proportion of patients fell into these categories (all < 3.0%).

OBJECTIVE 2: RELATIONSHIP BETWEEN OPIOID USE AND NEW-ONSET CM
A total of 31,730 patients met the inclusion/exclusion criteria (eg, EM with 24-month follow-up) for objective 2 and were included in the analyses. Among these patients, 2,996 (9.4%) transitioned to CM during the 24-month follow-up period. These 2,996 patients with new-onset CM had an CM= chronic migraine; EM = episodic migraine.

FIGURE 1
Patient Selection (continued)   TABLE 2 a cross-sectional, longitudinal Internet study that explored demographic and clinical characteristics associated with opioid use in migraine. 6 The study reported that opioid users were more likely to be male, had a higher body mass index, had a higher Total Pain Index score, had anxiety and depression, and had more than one cardiovascular comorbidity. Our study findings were generally similar, but two issues should be noted. First, in our study, a higher proportion of females fell into the 1-20 MME/day group and a higher proportion of males fell into the groups with at least 20 MME/day. In other words, in our study, females were more likely to use lower opioid doses and males were more likely to use higher opioid doses. Second, although our study found that patients who had more than 0 MME/day were more likely to have comorbidities than those with 0 MME/ day, the proportion of patients with some comorbidities least 90 MME/day. 15 A migraine-specific guideline on acute treatment by the American Headache Society indicated that opioids are not recommended for regular use in patients with migraine. 20 However, in this study, we found that about 7% of patients with CM with at least 1 opioid prescription had at least 50 MME/day in any 90-day period during the follow-up period, which shows that the guidelines have not been followed in some clinical practice. There has been expanding evidence identifying risk factors for new-onset CM in the past 2 decades, and a systematic review conducted by Buse et al was published in 2019. 5 The review summarized the available literature related to risk factors associated with progression from EM to CM. Factors with strong evidence included increased headache frequency, depression, and medication overuse. Consistent with this review, our study found that having a diagnosis of depression and MOH were significantly associated with higher hazard ratios of transitioning to CM during follow-up. In addition, our study found that having a diagnosis of fibromyalgia and back pain were also significantly associated with new-onset CM; these diagnoses are potentially additional modifiable risk factors that might provide targets for intervention.
The pattern of opioid use among patients with migraine and associated risk factors have been previously reported. 6 a At least 0 to less than 1 MME/day group includes those who did not use any opioids during follow-up, as well as those who used opioids but had an average daily MME less than 1 to accommodate patients with spurious opioid use. CM = chronic migraine; MME = morphine milligram equivalent.  did not increase monotonically with MME levels (eg, back pain, depression, or anxiety). This could imply that patients with extremely high opioid usage might receive opioid prescriptions for reasons other than disease severity.

LIMITATIONS
This study has several limitations. First, the database did not contain information regarding some potentially relevant variables (eg, frequency of headache days per month). For example, monthly headache frequency, disability, and some socioeconomic factors were not captured. As a consequence, this claim database analysis relied on ICD codes for diagnosis of CM or EM; however, it is possible that underdiagnosis or misdiagnosis could happen (eg, someone with tensiontype headache was mistakenly given an ICD code for EM). Second, because of the retrospective nature of the study, a causal relationship cannot be established. Third, most of the patients with EM did not transition to CM by the end of the 2-year follow-up. More longitudinal data might be helpful to capture the long-term progression process among patients with EM. Additionally, this study only captured prescription opioids from outpatient settings and may not include opioids that were given at inpatient or ED settings within hospitals. Moreover, the study included patients with continuous enrollment for up to 2 years who may have different characteristics or outcomes than patients who are more inclined to change their health plans. Additionally, this study used data up to December 31, 2018, and the clinical practice could have changed. Future researchers could evaluate the trend or change in opioid use pattern and migraine management in recent years. Finally, the study results might not be generalizable to patients who are not covered by commercial health plans